Artificial intelligence in medicine | 2019

Optimal testing policies for diagnosing patients with intermediary probability of disease

 
 
 
 

Abstract


This paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach derives an optimal policy whereby the decision maker is provided with a test strategy for each a priori probability of disease, aiming to reach posterior probabilities that warrant either immediate treatment or a not-ill diagnosis.

Volume 97
Pages \n 89-97\n
DOI 10.1016/j.artmed.2018.11.005
Language English
Journal Artificial intelligence in medicine

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